Patterns of Cognitive Strengths and Weaknesses and Relationships to Math Errors

Abstract

This study investigated cognitive patterns of strengths and weaknesses (PSW) and their relationship to patterns of math errors on the Kaufman Test of Educational Achievement (KTEA-3). Participants, ages 5 to 18, were selected from the KTEA-3 standardization sample if they met one of two PSW profiles: high crystallized ability (Gc) paired with low processing speed/long-term retrieval (Gs/Glr; n = 375) or high Gs/Glr paired with low Gc (n = 309). Estimates of Gc and Gs/Glr were based on five KTEA-3 subtests that measure either Gc (e.g., Listening Comprehension) or Gs/Glr (e.g., Object Naming Facility). The two groups were then compared on math error factors. Significant differences favored the High-Gc group for factors that measure math calculation, basic math concepts, and complex computation. However, the two groups did not differ in their errors on factors that measure geometry/measurement or simple addition. Results indicated that students with different PSW profiles also differed in the kinds of errors they made on math tests.

Patterns of Strengths and Weaknesses on the WISC-V, DAS-II, and KABC-II and Their Relationship to Students’ Errors in Oral Language, Reading, Writing, Spelling, and Math

“…As a result, students with similar broad ability profiles may have differed in their profile of narrow abilities, which could have increased heterogeneity within groups. In contrast to the findings of the present study, Liu et al (2017) found that particular profiles of strengths and weaknesses differentially predict error performance across several tests of reading and writing, and Koriakin et al (2017) found that particular profiles of strengths and weaknesses differentially predict error performance across tests of mathematics. The results of the present study along with the Liu et al and Koriakin et al studies suggest that the measures used to determine profiles may be an important sampling consideration for identifying group differences.…”

“…The lack of significant differences between cognitive profile groups on mathematics error factor scores was unexpected. A similar study conducted by Koriakin et al (2017) found significant differences between a group with High Gc (paired with low processing speed and/or long-term storage and retrieval) and a group with Low Gc (paired with high processing speed and/or longterm storage and retrieval) on three error factor scores: two error factors on Math Concepts & Applications (Math Calculation and Complex Math Problems) and one error factor on Math Computation (Basic Math Concepts). The Koriakin et al study used different measures of broad abilities to identify cognitive profiles (all measures were from the KTEA-3), which may have accounted for the lack of significant differences in this study.…”

Do Cognitive Patterns of Strengths and Weaknesses Differentially Predict Errors on Reading, Writing, and Spelling?

“…Burns (2016) and others have challenged the advocates of PSW to show these doubters the data. This study, when combined with data from a related PSW study that examined math errors (Koriakin et al, 2017), presents data to support the notion that students with different cognitive PSWs differ in the kinds of errors they make on tests of academic achievement. Naturally, further research is needed to extend these empirical findings and explore implications for instruction and educational interventions.…”

How Achievement Error Patterns of Students With Mild Intellectual Disability Differ From Low IQ and Low Achievement Students Without Diagnoses

“…This study soundly supports the concept of using evidence-based strategies for individuals with Mild ID, as well as exploring and capitalizing on known group areas of strength such as visual–spatial abilities (as exemplified on geometric concepts) and letter–sound knowledge in instruction. It is interesting to compare this study’s findings with the results of the Koriakin et al (2017) study, which examined differences in error patterns for students with distinct patterns of cognitive strength and weakness (PSW)—high crystallized/low memory speed versus high memory-speed/low crystallized. These researchers found that there were no significant differences between the PSW groups on KTEA-3 geometry-related problems, whereas there were significant differences on the other two error factor scores.…”